Data Analysis Flashcards

Flashcards for reviewing key concepts in data analysis, covering qualitative, quantitative, and mixed methods approaches.

Data Analysis

The systematic process of examining, organizing, and interpreting data to uncover patterns, relationships, and trends, enabling researchers to draw meaningful conclusions and support decision-making.

Qualitative Data Analysis

Focuses on interpreting non-numeric data (texts, images, audio, videos) to understand feelings, ideas, and reasons behind something.

Thematic Analysis

Identifies recurring themes or patterns in data, such as interviews or focus group transcripts.

Content Analysis

Systematically categorizes and codes textual data to quantify the presence of certain words, phrases, or concepts by counting how often they appear.

Narrative Analysis

Studies people’s stories to learn about their experiences and understand individual experiences or social phenomena.

Discourse Analysis

Examines language use in social contexts, such as political speeches or media content, to understand how people use language in different situations.

Quantitative Data Analysis

Involves working with numerical data to test hypotheses, identify patterns, or measure relationships using statistical techniques.

Descriptive Statistics

Organizes and summarizes data using numbers (e.g., mean).

Inferential Statistics

Makes predictions or inferences about a population based on a sample; data from a sample is used to draw conclusions about a larger group.

Data Visualization

Represents numerical data graphically to uncover patterns, trends, relationships, and insights using charts, graphs, and plots.

Predictive Analytics

Uses statistical, machine learning, and computational methods to analyze quantitative data and make predictions about future events or outcomes.

Mixed Methods Data Analysis

Combines qualitative (words) and quantitative (numbers) analysis to provide a fuller understanding of a problem.

Convergent Parallel Design

Studies qualitative and quantitative data separately and then combines the results.

Explanatory Sequential Design

Uses quantitative data first, then qualitative data to explain the numbers.

Exploratory Sequential Design

Starts with qualitative data and then uses quantitative data to confirm the ideas expressed.